In a multitude of commercial applications, it is common to employ a heavy duty conveyor belt for the purpose of transporting product and material. The conveyor belts so employed may be relatively long, for example, on the order of miles, and represent a high cost component of an industrial material handling operation. Such conveyor belts are often used to transport bulk material below and/or above ground, for example, in mining applications, which are often located in geographically remote locations. T he conveyor belts and respective drives are susceptible to normal wear and tear as well as damage firm the material being transported and/or harsh environmental conditions. In the event the conveyor belt or its drive system suffers catastrophic damage or otherwise become inoperable, the costs of repairing the conveyor belt, cleaning up spilt material and the downtime are substantial.
Thus, it is desirable to be able to first, predict a potential conveyor belt failure and second, stop the conveyor belt operation as soon as possible after a catastrophic failure has occurred. It is known to monitor various conveyor belt operating conditions and states, for example, belt position, speed, load, tension, rolling resistance, temperature, as well as detect a failure of a belt splice and the occurrence of a rip in the conveyor belt. Such monitoring of the conveyor belt operating conditions and states helps to detect conditions that may lead to belt damage and/or a catastrophic failure. Thus, there is currently some capability of quickly stopping a conveyor belt in the event of a catastrophic failure, for example, using rip detection; and there is some capability of detecting other potential failures. However, there are several disadvantages to the current systems.
First, current monitoring and analysis of conveyor belt operating conditions and states is performed at a site generally in the locality or vicinity of the conveyor belt. Further, current monitoring is generally analyzed most often by a user of the conveyor belt; however, the user often has less or more limited technical knowledge about the conveyor belt and its operation than., for example, a supplier of the conveyor belt system. Thus, since it is very expensive to bring a more knowledgeable technical person to the geographic location of the conveyor belt system, the ability to diagnose potential problems and take preventative measures is relatively limited with respect to any particular installed conveyor belt system. Further, the collection of data is generally limited to the operation of a single conveyor belt system; and there is no effective capability for collecting conveyor belt operating data from conveyor belt systems at geographically different sites. In addition, with such site-based systems, it is difficult to obtain and timely analyze data permitting an operational life of a conveyor belt to be maximized.
Hence, there is a need to expand the capabilities of current systems to permit a more comprehensive collection of conveyor belt operating data and permit that data to be analyzed and accessed by people with different interests at different global locations remote from the vicinity of the conveyor belt system.